Investigating the Effect of Facies Modeling and Seismic Data Integrating on Reducing the Uncertainty of Porosity Simulation in One of Iranꞌs Carbonate Reservoirs

Document Type : Research Paper

Authors

1 School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran

2 Department of Petrulom Oil and Gas, School of Chemical and Engineering, University of Tehran, Iran

Abstract

Facies are often imported in reservoir modeling because the petrophysical properties of interest are highly correlated with facies type. Knowledge of facies constrains the range of variability in porosity and other petrophysical properties. But on the other hand, proper study and modeling of facies requires considerable time and money in reservoir studies and also, due to the fact that the three-dimensional distribution of facies in many studies has not been able to significantly reduce uncertainty, Facial modeling has not received much attention, especially in carbonate reservoirs. In this study, after modeling the facies in a carbonate reservoir, comparison of porosity simulation has been performed using three-dimensional distribution of facies and without using it. In this study, SIS method was used to simulate facies and SGS method was used to porosity simulation. Also to investigate the reduction of model uncertainty with the seismic data integrating, Acoustics impedance has been used as secondary data in porosity simulation. Besides that, neural network analysis was performed on a set of seismic attributes to get facies probability cubes. These probability cubes was entered as a trend in the simulation of the facies. Examination of the error rate in blind wells showed that it is appropriate to use SIS and SGS geo-statistical methods in case of sufficient data in a carbonate reservoir and with the use of seismic data and the distribution of facies in porosity simulation, uncertainty was reduced to an acceptable level, with an average of 87% of the model being valid.
 

Keywords


[1]. Soleimani B, Nazari K, Bakhtiar H A, Haghparast G, Zandkarimi G, (2008) Three-dimensional geostatistical modeling of oil reservoirs: a case study from the ramin oil field in Iran, Journal of Applied Sciences, 8: 4523-4532.##
[2]. Osinowo O O, Ayorinde J O, Nwankwo C P, Ekeng O M, Taiwo O B (2018) Reservoir description and characterization of Eni field offshore Niger Delta, southern Nigeria, Journal Petrolum Exploration and Production Technology, 8, 2: 381–397. ##
[3]. Pyrcz M J, Deutsch C V (2014) Geostatistical reservoir modeling, Oxford University Press. ##
[4]. Cannon S (2018) Reservoir modelling: a practical guide, John Wiley and Sons Ltd All. ##
[5]. Ringrose P, Bentley M (2015) Reservoir model design: a practitioner›s guide, Springer Science and Business Media B.V. ##
[6]. Abd El-Gawad E A, Abdelwahhab M A, Bekiet M H, Noah A Z, ElSayed N A, Fouda A E (2019) Static reservoir modeling of El Wastani formation, for justifying development plans, using 2D seismic and well log data in Scarab field, offshore Nile Delta, Egypt, Journal of African Earth Sciences 158. ##
[7]. Dubrule O (2003) Geostatistics for seismic data integration in earth model, Society of Exploration Geophysics (SEG).
[8]. Emami Niri M, Lumley D E (2016) Estimation of subsurface geomodels by multi objective stochastic optimization, Journal of Applied Geophysics 129: 187–199. ##
[9]. Akanji A O, Sanuade O A, Kaka S I, Balogun I D (2018) Integration of 3D seismic and well log data for the exploration of kini field, offshore Niger delta, Petroleum and Coal 60,752–761. ##
[10]. Sanuade O A, Akanji A O, Oladunjoye M A, Olaojo A A, Fatoba JO (2017a) Hydrocarbon reservoir characterization of “AY” field, deep-water Niger Delta using 3D seismic and well logs, Arabian Journal of Geosciences 10: 151. ##
[11]. ShraggeJ, Bourget J, Lumley D, Giraud J, Wilson T, Iqbal A, Emami Niri M, Whitney B, Potter T, Miyoshi T, Witten B (2019) The Western Australia Modeling project—Part 1: Geomodel building, Interpretation, 7, 4:  T773–T791. ##
[12]. Hajikazemi E, Al-Aasm I S, Coniglio M (2010) Subaerial exposure and meteoric diagenesis of the Cenomanian-Turonian Upper Sarvak Formation, southwestern Iran, Geological Society, London, 330, 1: 253 – 272. ##
[13]. Hassanzadeh Azar J, M Nabi-Bidhendi, Javaherian A, Pishvaie M R (2009) Integrated seismic attributes to characterize a widely distributed carbonate clastic deposit system in Khuzestan Province, SW Iran, Journal of Geophysics and Engineering, Journal of Geophysics and Engineering, 6: 162-171. ##
[14]. Honarmand J, Nemati M, Monibi S (2009) Geological reservoir study of the Sarvak and Gadvan Formations in the Azadeganand Jufair Fields, wells AZN-8 and JR-4, Research Institute of Petroleum Industry, Unpublished Report, 174. ##
[15]. Randen T (2008) Mathematical methods and modelling in hydrocarbon exploration and production (mathematics in industry), Schlumberger Stavanger Research. ##
[16]. Mallet J L (2004) Space-time mathematical framework for sedimentary geology, Mathematical Geology, 36, 1: 1-32. ##
[17]. Yarus J M, Chambers R L, Mauces M, Shi G (2012) Facies simulation in practice: lithotype proportion mapping and plurigaussian simulation, a powerful combination, 9th International Geostatistics Congress, Oslo, Norway June 11 – 15. ##
[18]. Correia U M, Batezelli A, Leite E P (2016) 3-D Geological modelling: a siliciclastic reservoir case study from Campos Basin, Brazil, International Engineering Journal, 69, 4: 409-416. ##
[19]. Rahimi H, Asghari O, Hajizadeh F (2018) Selection of optimal thresholds for estimation and simulation based on indicator values of highly skewed distributions of ore data, Natural Resources Research. ##